The present disclosure relates to robotic systems for use in a warehouse or other environment. In many warehouse environments or supply chain environments, items have to be moved from one bin or container to another. The movement of items can be achieved through manual processes involving humans and/or the use of robots. A basic aspect of moving items involves picking as many objects from a source bin for distribution to multiple destination bins. Where humans are involved, much time is wasted when humans must locate and verify the right bins for transferring objects from bin to bin. Once the proper set of bins is identified, the human user wants to perform as many “picks” from the same source bin as possible.
Robotic warehouse systems have been developed to help manage this process in a way that is as automated as possible. Automated warehouses have some benefits over warehouses that use humans in some aspects of the process. However, a challenge that exists with respect to automated robotic systems is that they are designed for complete automation. In a completely automated robotic distribution system, typically the maximum amount of throughput is essentially fixed. Thus, if the system is designed to provide a maximum of movement of, say, 1000 items through the warehouse, it can become very difficult to scale up to higher amounts of throughput.
Accordingly, even with increased automation in warehouse environments, additional efficiencies and scalability issues still exist.